In this pilot study, we will do a systems genetics approach to power a genome wide association study (GWAS) to reveal loci associated with increased bacterial susceptibility. Vesicoureteric reflux (VUR) is estimated to effect 10% of children and predisposes them to urinary tract infections (UTI) with 40-70% of these children having an associated UTI. We hypothesize that we will be able to identify new loci underlying VUR and UTI susceptibility by categorizing and quantifying UTI with a novel bacterial imaging technique and subsequently GWAS. This will be possible utilizing the Hybrid Mouse Diversity Panel (HDMP) which is comprised of a wide range of genetic backgrounds. A similar approach was successful at identifying a locus potentially involved in VUR with a small set of animal and using the VUR phenotype to drive the analysis. However, we propose to use UTI, the highly associated disease of VUR, as the phenotype to identify the genetic pathways that predispose to VUR essentially dividing groups on natural ability to resist a urinary tract infection. In AIM1 we will categorize 50 fully sequenced mouse strains susceptible to pyelonephritis, the most severe form of UTI. The susceptible mice will be then tested for VUR. In AIM2, we will perform GWAS using the EMMA algorithm, using the categorical and quantitative phenotypes for VUR and UTI to identify candidate loci.